README.md

metadata

title: MCP GitHub PR Opportunity Server
emoji: 🔍
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: false
tag:
  - mcp-server-track
  - agent-demo-track
license: mit

Video Link: https://drive.google.com/file/d/1FaYPqtoYWmUBsjiSFexPNyPARvFsixsh/view?usp=sharing

MCP GitHub PR Opportunity Server

A Gradio-based MCP server that searches GitHub repositories for possible PR opportunities (open issues labeled 'good first issue' or 'help wanted'), supporting search by keyword and topic, with authentication.

Features

• Search GitHub repos by keyword and topic
• Find open issues labeled 'good first issue' or 'help wanted'
• Supports GitHub authentication via token
• Gradio MCP server for LLM integration
• Interactive web interface
• Compatible with n8n workflows

Local Setup

1. Clone the repo and install dependencies:

   cd mcp_github_server
   pip install -r requirements.txt
   

2. Configure GitHub Token:

   • Set GITHUB_TOKEN in your environment variables, or
   • Enter the token in the web interface

3. Run the server:

   python app.py
   

Hugging Face Spaces Deployment

1. Create a new Space:

   • Go to Hugging Face Spaces
   • Click "Create new Space"
   • Choose "Gradio" as the SDK
   • Name your space (e.g., "mcp-github-pr-server")

2. Configure Environment Variables:

   • In your Space settings, add GITHUB_TOKEN as a secret
   • Set your GitHub token as the value

3. Deploy:

   • Push your code to the Space repository
   • Hugging Face will automatically build and deploy your application

Using with MCP Clients

Add this configuration to your MCP client (e.g., Claude Desktop, Cursor, or Cline):

{
  "mcpServers": {
    "github-pr-finder": {
      "url": "https://akinyemiar-mcp-github-pr-server.hf.space/gradio_api/mcp/sse"
    }
  }
}

Using with n8n

1. Add HTTP Request Node:

   • In your n8n workflow, add an "HTTP Request" node
   • Set the URL to your Hugging Face Space URL (e.g., https://akinyemiar-mcp-github-pr-server.hf.space/api/predict)
   • Set Method to POST
   • Add Headers:

     Content-Type: application/json
     

   • Set Body to JSON:

     {
       "data": [
         "fastapi",
         "python",
         5,
         1,
         "YOUR_GITHUB_TOKEN"
       ]
     }
     

2. Process Response:

   • The response will contain opportunities and total_count
   • Use n8n's "Set" node to process the response data
   • Add additional nodes to handle the opportunities as needed

API Usage

The server provides both a web interface and an API endpoint at /api/predict. The API accepts POST requests with the following parameters:

{
  "data": [
    "keyword",     // optional
    "topic",       // optional
    "per_page",    // default: 5
    "page",        // default: 1
    "token"        // GitHub token
  ]
}

Response:

{
  "data": [
    {
      "opportunities": [
        {
          "repo_name": "tiangolo/fastapi",
          "repo_url": "https://github.com/tiangolo/fastapi",
          "issue_title": "Add more examples",
          "issue_url": "https://github.com/tiangolo/fastapi/issues/1234",
          "issue_labels": ["good first issue"],
          "issue_body": "Please add more examples to the docs..."
        }
      ],
      "total_count": 123
    }
  ]
}

License

MIT